Seasonal Ice Research Articles

Landfast Ice Controls on Turbulence in Antarctic Coastal Seas

AbstractKnowledge of the ocean surface layer beneath Antarctic landfast ice is sparse. In this article surface layer turbulent and fine structure are quantified with and without landfast ice at the same West Antarctic Peninsula location. Landfast ice reduced turbulence levels locally to an order of magnitude less than ice‐free values, and near‐inertial energy and sub‐inertial tidal energy levels to less than half their ice‐free values. Vertical turbulent heat and nutrient fluxes were, respectively, 6 and 10 times greater than previously estimated. Under‐ice tidal energy dissipation over the entire Antarctic continental shelf due to seasonal landfast ice cover is estimated to be between 788 MW to ∼6 GW. The total rate of wind‐generated turbulence in the surface ocean is greatly reduced by the presence of seasonal landfast ice to an average of 14% of the ice‐free value, but with large sectoral variations. Counter‐intuitively, however, tides and wind contribute approximately equally to the turbulent kinetic energy budget of the upper ocean between the Antarctic coastline and the maximal landfast ice extent, with large sectoral variations, attributed to geographic variations in the strength of the barotropic tide.

Turbulent Mixing in a Changing Arctic Ocean

Historically, the Arctic Ocean has been considered an ocean of low variability and weak turbulent mixing. However, the decline in seasonal sea ice cover over the past couple of decades has led to increased coupling between the atmosphere and the ocean, with potential enhancement of turbulent mixing. Here, we review studies that allow identifying energy sources and pathways that lead to turbulent mixing in an increasingly ice-free Arctic Ocean. We find that the evolution of wind-generated, near-inertial oscillations is highly sensitive to the seasonal sea ice cycle, but the response varies greatly between the continental shelves and the abyssal ocean and between the eastern and western ocean basins. There is growing interest in the role of tides and continental shelf waves in driving mixing over sloping topography. Both dissipate through the development of unsteady lee waves. The role eddies play in transporting shelf water into the basins and in supporting mixing has become more apparent as technological advances have permitted higher resolution observations of sea ice retreat. The importance of the dissipation of unsteady lee waves and of eddies in driving mixing highlights the need for parameterizations of these phenomena in regional ocean models and climate simulations.

A New Approach for the Estimation of Lake Ice Thickness From Conventional Radar Altimetry

Lake ice thickness (LIT), a thematic product of Lakes as an Essential Climate Variable (ECV), is sensitive to changes in air temperature and on-ice snow mass. Here, a novel and efficient analytic method (retracking approach) is presented for the estimation of LIT from Ku-band (13.6 GHz) radar altimetry data. The new retracker, referred to as LRM_LIT, is based on the physical modeling of the conventional radar echoes (also called Low Resolution Mode or LRM) over ice-covered lakes that show a characteristic step-like feature in their leading edge attributed to the reflection of radar waves at the snow-ice and ice-water interfaces. The method is applied to Jason-2 and Jason-3 data acquired over Great Slave Lake, Canada, over three ice seasons (2013-2016). As expected, the agreement between the Jason-2 and Jason-3 LIT estimates over their overlapping period (2016 ice season) is excellent with a mean bias error of 0.013 m and root mean square error (RMSE) of 0.024 m. LIT estimates from LRM_LIT are in good agreement with simulations from a thermodynamic lake ice model and in situ measurements with RMSE values of the order of few centimeters for the three winter seasons. The retracker also provides a robust way to assess the accuracy of LIT estimates which is in the order of 0.10 m when the ice cover is well established and prior to melt onset. In addition, LRM_LIT captures the seasonal transitions during the freeze-up and breakup periods and ice growth over different winter seasons, making it a promising method for monitoring inter-annual variability and trends in LIT from past and current conventional radar altimetry missions.

A Review of Arctic Sea Ice Climate Predictability in Large-Scale Earth System Models

We provide a high-level review of sea ice models used for climate studies and of the recent advances made with these models to understand sea ice predictability. Models currently in use for the Coupled Model Intercomparison Project and new developments coming online that will enable enhanced predictions are discussed. Previous work indicates that seasonal sea ice can be predicted based on mechanisms associated with long-lived ice thickness or ocean heat anomalies. On longer timescales, internal climate variability is an important source of uncertainty, although anthropogenic forcing is sizable, and studies suggest that anthropogenic signals have already emerged from internal climate noise. Using new analysis from the Multi-Model Large Ensemble, we show that while models differ in the magnitude and timing of predictable signals, many ice predictability characteristics are robust across multiple models. This includes the reemergence of predictable seasonal signals in ice area and the sizable uncertainty in predictions of ice-free Arctic timing associated with internal variability.

Winter thermal and ice regimes of small Karelian lakes against the background of regional climatic variability

This article investigates regularities of thermal and ice regimes of three small lakes of Karelia under current climatic conditions. Data of measurements of water temperature at autonomous stations and results of numerical calculations of the dates of ice-on and ice-off and the thickness of ice in these lakes using the one-dimensional parameterized model FLake in the anomalously warm winter season of 2019-2020 are analyzed. Data obtained are compared with long-term values over 1994-2019. The dates of the ice-on and ice-off on the lakes were quite close; however, on two larger lakes, intermediate ice destruction was observed at the beginning of winter, due to which the duration of the ice season differed between lakes by two weeks. The winter months of 2019-2020 were 6.4-9.4 ° C warmer than the baseline, which was reflected in a noticeably smaller ice thickness on the lakes compared to previous years of measurements (40-48 cm at the end of March 2020 compared to the values ​​in mid-April in 1994-2004 - 65-85 cm and in 2005-2018 - 50-65 cm). The decrease in ice thickness contributed to an early onset (mid-March) and long duration (more than five weeks) of spring subglacial convection. The model calculation, taking into account the atmospheric impact based on the ERA-5 re-analysis, reproduced the main features of the ice regime of the lakes, including the intermediate destruction of ice at the beginning of winter on two larger lakes. Significant regression relationships have been obtained between the dates of ice-on and ice-off on Lake Vendyurskoe, the dates of the onset and duration of spring under-ice convection, and the characteristics of the regional climate of southern Karelia (air temperature and the number of days with thaw in winter and spring months) for 1994-2020. The relationship between the dates of ice-on and the water temperature in the lake in winter is shown.

Гидрометеорологические опасные природные явления Северного Каспия в зимний период на фоне климатических изменений

Hydrometeorological hazards of the Northern Caspian during the winter periods 1950–2020—due to climatic changes were investigated. Hydrometeorological hazards for the period 1950–2020 are considered: severe winter periods, early ice freeze-up, storm waves, wind surge, as well as cumulative hydrometeorological hazards—combinations of storm waves and surge. Geographic information system (GIS) “Ice regime of the southern seas of Russia” is the information basis for the study of the ice regime of the Caspian Sea. Storm activity in the Caspian Sea were reconstructed using SWAN spectral wave model. Based on the cumulative freezing-degree days winters were divided by severity—mild, moderate and severe. During the study period, moderate types of winters prevail (59.4 %), and the number of severe and mild winters is the same and amounts to 14 pcs. (20.3 %) of each type. Due to climate change, the number of mild winters is increasing, and the number of severe ones is decreasing. Since 1985, 3 severe winters (2002/03, 2007/08, 2011/12) have been recorded. As a result, the ice cover area decreased by ∼7–10 %, and the duration of the ice season at the observation point Peshnoy was reduced by 5 days. 157 situations of combinations of storm surge and storm waves are identified: 140 are cases of potential situations of cumulative phenomena of a combination of storm and surge phenomena with a speed of 15 m/s or more of winds of effective directions. The largest number of cases of cumulative dangerous hydrometeorological hazards with a wind speed of more than 15 m/s is observed in March. After the 2000s there was an increase in the number of cases and duration of dangerous hydrometeorological hazards in November and March. A direct relationship between the number of cases of cumulative dangerous hydrometeorological hazards and the severity of winters has not been found.

Сравнительный анализ данных ледовитости Берингова моря по данным Sea Ice Index и Masie

This paper presents a comparative analysis of the ice cover of the Bering Sea. The analysis was performed according to the National Snow & Ice Data Center (NSIDC) using NASA algorithms Team (Sea Ice Index) and Near-Real-Time Passive Microwave/Visible Data Sharing DMSP SSMIS Daily Polar gridded Sea Ice Concentrations and Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data (MASIE-NH). The absolute and relative difference of the ice cover values were calculated using the algorithms Sea Ice Index and MASIE-NH with daily discreteness for 14 ice seasons from 2006 to 2020. Despite the fact that the spatial resolutions of the data of the algorithms under consideration and the quantitative criteria for the condition for classifying a pixel as pure water or ice extent differed (the side of the pixel was 25 and 4 km, identification was 15 and 40 %, respectively), the curves of the average seasonal variation of the ice cover were in phase and that was confirmed by the high value of the correlation coefficient (0.92). It was determined that the difference in ice cover values were not critical and were within the calculation limits, which allowed using data from both sources without calculating correction factors. Sea Data Ice Index data should be appropriate for long-term analysis of inter-seasonal variability, since data series of observations with daily discreteness have been available since 1978. It was concluded that the use of both sources would be quite acceptable in the analysis of intra-seasonal fluctuations. A characteristic feature of Sea Ice Index was noted—the presence of ice throughout the warm season. Although according to literary sources, such a phenomenon in the Bering Sea was typical only for severe types of winters. That was probably due to the technical difficulties in identifying the ice extent using passive microwave sounding methods.

Seasonal ice dynamics in the lower ablation zone of Dagongba Glacier, southeastern Tibetan Plateau, from multitemporal UAV images

AbstractMost glaciers on the Tibetan Plateau have experienced continuous mass losses in response to global warming. However, the seasonal dynamics of glaciers on the southeastern Tibetan Plateau have rarely been reported in terms of glacier surface elevation and velocity. This paper presents a first attempt to explore the seasonal dynamics of the debris-covered Dagongba Glacier within the southeastern Tibetan Plateau. We use the multitemporal unoccupied aerial vehicle images collected over the lower ablation zone on 8 June and 17 October 2018, and 13 May 2019, and then perform an analysis concerning climatic fluctuations. The results reveal that the mean surface elevation decrease of the Dagongba Glacier during the warm season ($2.81\pm 0.44$ m) was remarkably higher than the cold season ($0.72\pm 0.45$ m). Particularly notable glacier surface elevation changes were found around supraglacial lakes and ice cliffs where ice ablation rates were $\sim$3 times higher than the average. In addition, a larger longitudinal decline of glacier surface velocity was observed in the warm season than that in the cold season. In terms of further comparative analysis, the Dagongba Glacier experienced a decrease in surface velocity between 1982–83 and 2018–19, with a decrease in the warm season possibly twice as large as that in the cold season.

Seasonal Variations and Drivers of Surface Ocean pCO2 in the Seasonal Ice Zone of the Eastern Indian Sector, Southern Ocean

AbstractTo quantitatively assess the inorganic carbon cycle in the eastern Indian sector of the Southern Ocean (80–150°E, south of 60°S), we measured ocean surface temperature, salinity, total alkalinity (TA), the partial pressure of carbon dioxide (pCO2), and concentrations of chlorophyll‐a (chl a), dissolved inorganic carbon (DIC), and nutrients during the KY18 survey (December 2018–January 2019). The sea–air CO2 flux in this region was −8.3 ± 12.7 mmol m−2 day−1 (−92.1 to +10.6 mmol m−2 day−1). The ocean was therefore a weak CO2 sink. Based on the DIC and TA in the temperature minimum layer, we estimated the change of pCO2 from winter to summer (δpCO2) due to changes in water temperature, salinity, and biological activity (photosynthesis). The spatial distribution of pCO2 in the western part (80–110°E) of the study area was mainly driven by biological activity, which decreased pCO2 from December to early January, and in the eastern part (110–150°E) by temperature, which increased pCO2 from January to February. We also examined the changes in the CO2 concentrations (xCO2) over time by comparing data from 1996 with our data (2018–2019). The oceanic and atmospheric xCO2 increased by 23 and 45 ppm in 23 years, respectively. These changes of ocean xCO2 were mainly driven by an increase in CO2 uptake from the atmosphere as a result of the rise in atmospheric xCO2 and increase in biological activity associated with the change in the water‐mass distribution.

Intercomparison of Salinity Products in the Beaufort Gyre and Arctic Ocean

Salinity is the primary determinant of the Arctic Ocean’s density structure. Freshwater accumulation and distribution in the Arctic Ocean have varied significantly in recent decades and certainly in the Beaufort Gyre (BG). In this study, we analyze salinity variations in the BG region between 2012 and 2017. We use in situ salinity observations from the Seasonal Ice Zone Reconnaissance Surveys (SIZRS), CTD casts from the Beaufort Gyre Exploration Project (BGP), and the EN4 data to validate and compare with satellite observations from Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), and Aquarius Optimally Interpolated Sea Surface Salinity (OISSS), and Arctic Ocean models: ECCO, MIZMAS, HYCOM, ORAS5, and GLORYS12. Overall, satellite observations are restricted to ice-free regions in the BG area, and models tend to overestimate sea surface salinity (SSS). Freshwater Content (FWC), an important component of the BG, is computed for EN4 and most models. ORAS5 provides the strongest positive SSS correlation coefficient (0.612) and lowest bias to in situ observations compared to the other products. ORAS5 subsurface salinity and FWC compare well with the EN4 data. Discrepancies between models and SIZRS data are highest in GLORYS12 and ECCO. These comparisons identify dissimilarities between salinity products and extend challenges to observations applicable to other areas of the Arctic Ocean.

Autonomous System for Lake Ice Monitoring.

Continuous monitoring of ice cover belongs to the key tasks of modern climate research, providing up-to-date information on climate change in cold regions. While a strong advance in ice monitoring worldwide has been provided by the recent development of remote sensing methods, quantification of seasonal ice cover is impossible without on-site autonomous measurements of the mass and heat budget. In the present study, we propose an autonomous monitoring system for continuous in situ measuring of vertical temperature distribution in the near-ice air, the ice strata and the under-ice water layer for several months with simultaneous records of solar radiation incoming at the lake surface and passing through the snow and ice covers as well as snow and ice thicknesses. The use of modern miniature analog and digital sensors made it possible to make a compact, energy efficient measurement system with high precision and spatial resolution and characterized by easy deployment and transportation. In particular, the high resolution of the ice thickness probe of 0.05 mm allows to resolve the fine-scale processes occurring in low-flow environments, such as freshwater lakes. Several systems were tested in numerous studies in Lake Baikal and demonstrated a high reliability in deriving the ice heat balance components during ice-covered periods.

A Cloudier Picture of Ice-Albedo Feedback in CMIP6 Models

Increased solar absorption is an important driver of Arctic Amplification, the interconnected set of processes and feedbacks by which Arctic temperatures respond more rapidly than global temperatures to climate forcing. The amount of sunlight absorbed in the Arctic is strongly modulated by seasonal ice and snow cover. Sea ice declines and shorter periods of seasonal snow cover in recent decades have increased solar absorption, amplifying local warming relative to the planet as a whole. However, this Arctic albedo feedback would be substantially larger in the absence of the ubiquitous cloud cover that exists throughout the region. Clouds have been observed to mask the effects of reduced surface albedo and slow the emergence of secular trends in net solar absorption. Applying analogous metrics to several models from the 6thClimate Model Intercomparison Project (CMIP6), we find that ambiguity in the influence of clouds on predicted Arctic solar absorption trends has increased relative to the previous generation of climate models despite better agreement with the observed albedo sensitivity to sea ice variations. Arctic albedo responses to sea ice loss are stronger in CMIP6 than in CMIP5 in all summer months. This agrees better with observations, but models still slightly underestimate albedo sensitivity to sea ice changes relative to observations. Never-the-less, nearly all CMIP6 models predict that the Arctic is now absorbing more solar radiation than at the start of the century, consistent with recent observations. In fact, many CMIP6 models simulate trends that are too strong relative to internal variability, and spread in predicted Arctic albedo changes has increased since CMIP5. This increased uncertainty can be traced to increased ambiguity in how clouds influence natural and forced variations in Arctic solar absorption. While nearly all CMIP5 models agreed with observations that clouds delay the emergence of forced trends, about half of CMIP6 models suggest that clouds accelerate their emergence from natural variability. Isolating atmospheric contributions to total Arctic reflection suggests that this diverging behavior may be linked to stronger Arctic cloud feedbacks in the latest generation of climate models.

Experimental and Numerical Research on the Performance of a Seasonal Ice Storage Device in Summer Residential Rooms of Northeast China

• A 3D transient simulation of Seasonal Ice Storage Device is performed. • Experimental study is conducted to storage energy. • The impacts of various affecting factors on the performance of the ice making and storage device are analyzed. • The optimum size and energy saving potential of the device are given. Seasonal cold storage is an environment-friendly technique that utilizes natural cold source in winter for summer cooling. In this study, a seasonal ice storage device using cold ambient air in cold regions in winter to make and storage ice for cooling residential rooms in summer was developed. The mathematical model of a seasonal ice storage device was established and validated though designing and measuring the operation data of an experimental device under the winter condition in Shenyang, China. The impacts of various affecting factors, including the inlet wind speed, inlet size, and the air channel size on the performance of the ice making and storage device were analyzed. The results indicate that the time that is taken for ice-making decreases with the increase of the inlet size, decreases with the increase of the inlet wind speed and decreases with the increase of the air channel size. The optimal air channel size of the seasonal ice storage device was achieved. The proposed and optimized device can save cold energy for residential buildings, and provide some guidance for the understanding of ice making and ice storage characteristics in the seasonal ice storage device.

Sea-ice derived meltwater stratification slows the biological carbon pump: results from continuous observations

The ocean moderates the world’s climate through absorption of heat and carbon, but how much carbon the ocean will continue to absorb remains unknown. The North Atlantic Ocean west (Baffin Bay/Labrador Sea) and east (Fram Strait/Greenland Sea) of Greenland features the most intense absorption of anthropogenic carbon globally; the biological carbon pump (BCP) contributes substantially. As Arctic sea-ice melts, the BCP changes, impacting global climate and other critical ocean attributes (e.g. biodiversity). Full understanding requires year-round observations across a range of ice conditions. Here we present such observations: autonomously collected Eulerian continuous 24-month time-series in Fram Strait. We show that, compared to ice-unaffected conditions, sea-ice derived meltwater stratification slows the BCP by 4 months, a shift from an export to a retention system, with measurable impacts on benthic communities. This has implications for ecosystem dynamics in the future warmer Arctic where the seasonal ice zone is expected to expand.

Assessing the importance of bi-directional melting when modeling boreal peatland freeze/thaw dynamics

The modeling of seasonal ground ice (SGI) freeze/thaw a common feature in boreal peatlands, has often been completed using a unidirectional approach, where melting is driven by energy inputs from the surface. However, bi-directional melt is known to occur, and can potentially increase the spring melt rate. Accurate modelling of the timing of ice-free conditions in peatlands is important because SGI can impede spring infiltration and lead to substantial spring snowmelt runoff from peatlands. However, when modelling melt only from above, erroneous results in the model estimation of ice-free conditions can occur, which can lead to knock on-effects for modelling peatland hydrological function. Furthermore, as the climate warms, it is unclear how this role of SGI may change in the future. This study used the Stefan Equation to model unidirectional and bi-directional melt to assess which performed better in modelling the timing of ice-free conditions compared to observed values (BI: 3.9 ± 2.1 days, UNI: 9.0 ± 4.7). Including bi-directional melt improved model performance by reducing this difference by approximately 5 days. Model performance for SGI freeze/thaw cycles were similar, with BI being slightly more accurate in freezing (RMSE:2.7 cm versus 3.3 cm) and melting (RMSE: 2.6 cm vs 3.7 cm) compared to the unidirectional approach. While the model improvement in the timing of ice-free conditions was substantial, careful consideration is needed in determining when a peatland is functionally ice free in future modelling studies. The Stefan Equation was found to be most sensitive to changes in soil moisture, compared to ground surface temperature and peat porosity, likely due to the relationship between thermal conductivity and frozen and liquid water content. Comparisons with future climate change projections suggest that the timing of ice-free conditions could shift by as much as 2 weeks earlier in the 2050′s and by almost a month earlier in the 2080′s. However, the timing of snowfall, and rain on snow events continues to be a source of model uncertainty. Future studies should work to investigate the potential positive feedbacks this could create. In conclusion, the Stefan Equation presents a relatively easy path for incorporating bi-directional melt into peatland models. This process should be included in peatland ecohydrological models in order to properly model the timing of melt and ice-free conditions.

Landfast Ice and Coastal Wave Exposure in Northern Alaska

AbstractObservations of ocean surface waves at three sites along the northern coast of Alaska show a strong correlation with seasonal sea ice patterns. In the winter, ice cover is complete, and waves are absent. In the spring and early summer, sea ice retreats regionally, but landfast ice persists near the coast. The landfast ice completely attenuates waves formed farther offshore in the open water, causing up to a two‐month delay in the onset of waves near shore. In autumn, landfast ice begins to reform, though the wave attenuation is only partial due to lower ice thickness compared to spring. The annual cycle in the observations is reproduced by the ERA5 reanalysis product, but the product does not resolve landfast ice. The resulting ERA5 bias in coastal wave exposure can be corrected by applying a higher‐resolution ice mask, and this has a significant effect on the long‐term trends inferred from ERA5.

Landfast sea ice in the Bothnian Bay (Baltic Sea) as a temporary storage compartment for greenhouse gases

Although studies of biogeochemical processes in polar sea ice have been increasing, similar research on relatively warm low-salinity sea ice remains sparse. In this study, we investigated biogeochemical properties of the landfast sea ice cover in the brackish Bothnian Bay (Northern Baltic Sea) and the possible role of this sea ice in mediating the exchange of greenhouse gases, including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) across the water column–sea ice–atmosphere interface. Observations of total alkalinity and dissolved inorganic carbon in both landfast sea ice and the water column suggest that the carbonate system is mainly driven by salinity. While high CH4 and N2O concentrations were observed in both the water column (up to 14.3 and 17.5 nmol L–1, respectively) and the sea ice (up to 143.6 and 22.4 nmol L–1, respectively), these gases appear to be enriched in sea ice compared to the water column. This enrichment may be attributable to the sea ice formation process, which concentrates impurities within brine. As sea ice temperature and brine volume decrease, gas solubility decreases as well, promoting the formation of bubbles. Gas bubbles originating from underlying sediments may also be incorporated within the ice cover and contribute to the enrichment in sea ice. The fate of these greenhouse gases within the ice merits further research, as storage in this low-salinity seasonal sea ice is temporary.

Effects of Climate Change on River-Ice Processes and Ice Jams

As the climate changes, ice characteristics and river-ice processes are altered, sometimes in unexpected ways. A warmer climate will obviously result in less ice globally, and in a general northward shift in the limits of seasonal river-ice occurrence. However, in several watersheds, the frequency of midwinter breakup events and the intensity of breakup ice jams may also change. In addition, climate change will alter other river-ice processes such as ice formation, freeze-up jams, and hanging dams. This is of concern during the design and construction of infrastructure as well as during the planning and implementation of flood-damage-reduction measures in and along rivers with seasonal ice covers. Changes in river-ice regimes will also alter the ecology of many lotic systems. The paper reviews potential effects of a changing climate on river-ice properties and processes, and provides a discussion of future outcomes and their significance, as well as a suggested direction for future cold-regions river research.

Sea ice presence is linked to higher carbon export and vertical microbial connectivity in the Eurasian Arctic Ocean

Arctic Ocean sea ice cover is shrinking due to warming. Long-term sediment trap data shows higher export efficiency of particulate organic carbon in regions with seasonal sea ice compared to regions without sea ice. To investigate this sea-ice enhanced export, we compared how different early summer phytoplankton communities in seasonally ice-free and ice-covered regions of the Fram Strait affect carbon export and vertical dispersal of microbes. In situ collected aggregates revealed two-fold higher carbon export of diatom-rich aggregates in ice-covered regions, compared to Phaeocystis aggregates in the ice-free region. Using microbial source tracking, we found that ice-covered regions were also associated with more surface-born microbial clades exported to the deep sea. Taken together, our results showed that ice-covered regions are responsible for high export efficiency and provide strong vertical microbial connectivity. Therefore, continuous sea-ice loss may decrease the vertical export efficiency, and thus the pelagic-benthic coupling, with potential repercussions for Arctic deep-sea ecosystems.

Sea ice in the northern North Atlantic through the Holocene: Evidence from ice cores and marine sediment records

Sea ice plays a pivotal role in Earth's climate and its past reconstruction is crucial to investigate the connections and feedbacks with the other components of the climate system. Among the available archives that store information of past sea ice are marine and ice cores. Recent studies on the IP25 biomarker extracted from marine sediments has shown great skill to infer past changes of Arctic sea ice. In ice matrixes, sodium, bromine and iodine have shown potential to store the fingerprint of sea ice presence. The development of an unambiguous sea ice proxy from ice cores, however, has proven to be a challenging task especially in the Arctic realm.In this work we analyze the sodium, bromine and iodine records in the RECAP ice core, coastal eastern Greenland, to investigate the sea ice variability in the northern North Atlantic Ocean through the last 11,000 years of the current interglacial, i.e. the Holocene. We compare the RECAP records with marine sea ice proxy records available from the northern North Atlantic.We suggest that RECAP sodium concentrations can be associated with variability of sea ice extent, while the bromine-to-sodium ratios and iodine are associated respectively with seasonal sea ice and bioproductivity from open ocean and fresh sea ice surfaces.According to our interpretation, we find that sea ice was at its lowest extent and seasonal in nature during the early Holocene in all regions of the North Atlantic. Increasing sea ice signals are seen from ca. 8–9 ka b2k, in line with long-term Holocene cooling. The increasing sea ice trend appears uninterrupted in the Fram Strait and North Iceland while reaching a maximum ca. 5 ka b2k in the East Greenland region. Sea ice modifications during the last 5000 years display great variability in East Greenland with intermediate conditions between the early and mid Holocene, possibly associated with local fjord dynamics. The last sea ice maximum was reached across all regions 1000 years b2k.